
where \(g_{\pi }\)  is the pre-processing model,
\({\mathbf {\omega }}_{m}\)  and \({\mathbf {a}}_{m}\)  the pre-processed measurements, commonly approximated by
linear models, e.g., bias model: [1]}, [2]}, [3]}:
\({\mathbf {\omega }}_m \!=\! {^I}{\mathbf {\omega }} \!+\! {\mathbf {b}}_g \!+\! {\mathbf {n}}_g,\,\,\,{\mathbf {a}}_m \!=\! {^I}{\mathbf {a}} \!+ \!{\mathbf {b}}_a \!+\! {\mathbf {n}}_a\) 
